{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Cyclicals\n",
    "### Summary \n",
    "\n",
    "With growing focus on cyclical asset recovery and a still very easy stance from the Fed, the short USD theme has gotten renewed attention from the investor community.\n",
    "\n",
    "In the analysis below, we look at G10 currencies' correlation to risk (proxied by SPX) and volatility and find that NOK offers both high exposure to a continued risk-on rally with cheap tails compared to peers.\n",
    "\n",
    "P.S. Missed our webcast? [Click here](https://developer.gs.com/docs/gsquant/videos/gs-quant-meets-markets-nov/) for a replay that touches on this theme. Also checkout [this note](https://marquee.gs.com/content/markets/en/2020/11/25/bbe0fca7-c70b-4c92-a0f3-22880574d957.html) from Brian Friedman for specific implementations of this theme.\n",
    "\n",
    "The content of this notebook is split into:\n",
    "* [1 - Let's get started with gs quant](#1---Let's-get-started-with-gs-quant)\n",
    "* [2 - Find cyclical crosses](#2---Find-cyclical-crosses)\n",
    "* [3 - Solve for best expression](#3---Solve-for-best-expresion)\n",
    "* [What's New](#What's-New)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 1 - Let's get started with gs quant\n",
    "Start every session with authenticating with your unique client id and secret. If you don't have a registered app, create one [here](https://marquee.gs.com/s/developer/myapps/register). `run_analytics` scope is required for the functionality covered in this example. Below produced using gs-quant version 0.8.227."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gs_quant.session import GsSession\n",
    "# external users should substitute their client id and secret; please skip this step if using internal jupyterhub\n",
    "GsSession.use(client_id=None, client_secret=None, scopes=('run_analytics',)) "
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 2 - Find cyclical crosses\n",
    "\n",
    "Let's start by looking for crosses that are most sensitive to risk. To do that, we use SPX returns as the risk proxy and look at the YTD relationship of each cross' weekly returns to SPX's. We pull the FX spot data from FRED ([create token here](https://research.stlouisfed.org/docs/api/api_key.html) if you don't have one), downsample data from daily to weekly and calculate returns at a first step. FX spot also available via [gs data catalog](https://marquee.web.gs.com/s/developer/datasets/FXSPOT_PREMIUM/connect)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>SPX</th>\n",
       "      <th>EUR</th>\n",
       "      <th>JPY</th>\n",
       "      <th>AUD</th>\n",
       "      <th>GBP</th>\n",
       "      <th>CAD</th>\n",
       "      <th>NOK</th>\n",
       "      <th>CHF</th>\n",
       "      <th>SEK</th>\n",
       "      <th>NZD</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>date</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>2020-01-10</th>\n",
       "      <td>0.94</td>\n",
       "      <td>-0.48</td>\n",
       "      <td>-1.42</td>\n",
       "      <td>-0.86</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>-0.51</td>\n",
       "      <td>-0.76</td>\n",
       "      <td>-0.27</td>\n",
       "      <td>-1.26</td>\n",
       "      <td>-0.51</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-17</th>\n",
       "      <td>1.97</td>\n",
       "      <td>-0.23</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>-0.38</td>\n",
       "      <td>-0.24</td>\n",
       "      <td>-0.18</td>\n",
       "      <td>-0.31</td>\n",
       "      <td>0.48</td>\n",
       "      <td>-0.11</td>\n",
       "      <td>-0.44</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2020-01-24</th>\n",
       "      <td>-1.03</td>\n",
       "      <td>-0.60</td>\n",
       "      <td>0.78</td>\n",
       "      <td>-0.77</td>\n",
       "      <td>0.32</td>\n",
       "      <td>-0.55</td>\n",
       "      <td>-1.39</td>\n",
       "      <td>-0.30</td>\n",
       "      <td>-0.53</td>\n",
       "      <td>-0.12</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "             SPX   EUR   JPY   AUD   GBP   CAD   NOK   CHF   SEK   NZD\n",
       "date                                                                  \n",
       "2020-01-10  0.94 -0.48 -1.42 -0.86 -0.24 -0.51 -0.76 -0.27 -1.26 -0.51\n",
       "2020-01-17  1.97 -0.23 -0.60 -0.38 -0.24 -0.18 -0.31  0.48 -0.11 -0.44\n",
       "2020-01-24 -1.03 -0.60  0.78 -0.77  0.32 -0.55 -1.39 -0.30 -0.53 -0.12"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from gs_quant.data import Dataset\n",
    "from gs_quant.api.fred.data import FredDataApi\n",
    "from gs_quant.timeseries import returns\n",
    "from datetime import date\n",
    "import pandas as pd\n",
    "pd.set_option('display.precision', 2)\n",
    "\n",
    "data = {'SPX': 'SP500', 'EUR': 'DEXUSEU', 'JPY': 'DEXJPUS', 'AUD': 'DEXUSAL', 'GBP': 'DEXUSUK', 'CAD': 'DEXCAUS',\n",
    "       'NOK': 'DEXNOUS', 'CHF': 'DEXSZUS', 'SEK': 'DEXSDUS', 'NZD': 'DEXUSNZ'}\n",
    "pairs = {'EUR': 'EURUSD', 'JPY': 'USDJPY', 'AUD': 'AUDUSD', 'GBP': 'GBPUSD', 'CAD': 'USDCAD', 'NOK': 'USDNOK',\n",
    "        'CHF': 'USDCHF', 'SEK': 'USDSEK', 'NZD': 'NZDUSD'}\n",
    "\n",
    "FRED_API_KEY = 'YOUR_KEY_HERE'\n",
    "fred_API = FredDataApi(api_key=FRED_API_KEY)\n",
    "df = pd.concat([Dataset(symbol, fred_API).get_data(date(2020, 1, 1)) for n, symbol in data.items()], axis=1)\n",
    "df.columns = data.keys()\n",
    "# let's flip these to look at all relative to USD\n",
    "df = df.apply(lambda x: 1/x if x.name in ['JPY', 'CAD', 'SEK', 'NOK', 'CHF'] else x)\n",
    "rets = returns(df.resample('W-FRI').last(), 1).dropna()\n",
    "rets.head(3) * 100"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "With the data in hand, let's look at the relationship of SPX to the other pairs in order of the highest r-squared which represent the strongest relationship to SPX. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:title={'center':'YTD R^2 with SPX'}>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "from scipy.stats import pearsonr\n",
    "\n",
    "crosses = list(pairs.keys())\n",
    "r2 = pd.Series({i: pearsonr(rets.SPX, rets[i])[0] for i in crosses}, name='R2').sort_values(ascending=False)\n",
    "r2.plot(kind='bar', title='YTD R^2 with SPX')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As we can see above, AUD, NOK and CAD have the top 3 highest correlations to SPX YTD.\n",
    "\n",
    "To visually confirm that the relationship is not driven by tail events let's look at a scatter; returns on weeks where SPX has realized greater or less than 10% are denoted in green and red, respectively. The below confirms the relationship still holds especially for the top 3 crosses."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<seaborn.axisgrid.PairGrid at 0x213359c67c8>"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1416.25x180 with 11 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import seaborn as sns\n",
    "\n",
    "rets['spx_thres'] = rets.SPX.apply(lambda x: '>10%' if x >=.1 else '<10%' if x <=-.1 else '')\n",
    "sns.pairplot(rets, y_vars=['SPX'], x_vars=r2.keys().insert(0, 'SPX'), hue='spx_thres', aspect=.75)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 3 - Solve for Best Expression\n",
    "\n",
    "Now let's see how far out-of-the-money we need to strike binaries to express a short dollar view and get a 10x payout (note - you can use any ratio below). P.S. You can find more screens like this in our brand new [reports and screens folder](https://nbviewer.jupyter.org/github/goldmansachs/gs-quant/tree/master/gs_quant/content/reports_and_screens)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "from gs_quant.markets import PricingContext\n",
    "from gs_quant.markets.portfolio import Portfolio\n",
    "from gs_quant.instrument import FXBinary\n",
    "from gs_quant.risk import FXSpot\n",
    "\n",
    "payout_ratio = '10%'\n",
    "\n",
    "binaries = Portfolio([FXBinary(pair=cross, expiration_date='3m', option_type='Put' if cross[:3]=='USD' else 'Call',\n",
    "                               notional_currency='USD', strike_price=f'p={payout_ratio}', premium=0, name=ccy)\n",
    "                      for ccy, cross in pairs.items()])\n",
    "with PricingContext():   \n",
    "    binaries.resolve()\n",
    "    spot = binaries.calc(FXSpot)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style  type=\"text/css\" >\n",
       "    #T_12672f68_33f8_11eb_963b_00505611250crow0_col6 {\n",
       "            background-color:  #fff7fb;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow1_col6 {\n",
       "            background-color:  #9cb9d9;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow2_col6 {\n",
       "            background-color:  #9cb9d9;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow3_col6 {\n",
       "            background-color:  #7eadd1;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow4_col6 {\n",
       "            background-color:  #6fa7ce;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow5_col6 {\n",
       "            background-color:  #5ea0ca;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow6_col6 {\n",
       "            background-color:  #4a98c5;\n",
       "            color:  #000000;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow7_col6 {\n",
       "            background-color:  #045280;\n",
       "            color:  #f1f1f1;\n",
       "        }    #T_12672f68_33f8_11eb_963b_00505611250crow8_col6 {\n",
       "            background-color:  #023858;\n",
       "            color:  #f1f1f1;\n",
       "        }</style><table id=\"T_12672f68_33f8_11eb_963b_00505611250c\" ><thead>    <tr>        <th class=\"blank level0\" ></th>        <th class=\"col_heading level0 col0\" >option_type</th>        <th class=\"col_heading level0 col1\" >strike_price</th>        <th class=\"col_heading level0 col2\" >spot</th>        <th class=\"col_heading level0 col3\" >R2</th>        <th class=\"col_heading level0 col4\" >realized_vol</th>        <th class=\"col_heading level0 col5\" >% otms</th>        <th class=\"col_heading level0 col6\" >% otms (vol norm)</th>    </tr>    <tr>        <th class=\"index_name level0\" >pair</th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>        <th class=\"blank\" ></th>    </tr></thead><tbody>\n",
       "                <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row0\" class=\"row_heading level0 row0\" >USD NOK</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col0\" class=\"data row0 col0\" >OptionType.Put</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col1\" class=\"data row0 col1\" >8.28</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col2\" class=\"data row0 col2\" >8.86</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col3\" class=\"data row0 col3\" >0.82</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col4\" class=\"data row0 col4\" >18.18</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col5\" class=\"data row0 col5\" >6.59</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow0_col6\" class=\"data row0 col6\" >0.36</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row1\" class=\"row_heading level0 row1\" >AUD USD</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col0\" class=\"data row1 col0\" >OptionType.Call</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col1\" class=\"data row1 col1\" >0.78</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col2\" class=\"data row1 col2\" >0.74</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col3\" class=\"data row1 col3\" >0.82</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col4\" class=\"data row1 col4\" >13.02</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col5\" class=\"data row1 col5\" >5.83</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow1_col6\" class=\"data row1 col6\" >0.45</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row2\" class=\"row_heading level0 row2\" >NZD USD</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col0\" class=\"data row2 col0\" >OptionType.Call</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col1\" class=\"data row2 col1\" >0.74</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col2\" class=\"data row2 col2\" >0.70</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col3\" class=\"data row2 col3\" >0.77</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col4\" class=\"data row2 col4\" >13.03</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col5\" class=\"data row2 col5\" >5.84</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow2_col6\" class=\"data row2 col6\" >0.45</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row3\" class=\"row_heading level0 row3\" >USD CAD</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col0\" class=\"data row3 col0\" >OptionType.Put</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col1\" class=\"data row3 col1\" >1.25</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col2\" class=\"data row3 col2\" >1.30</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col3\" class=\"data row3 col3\" >0.77</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col4\" class=\"data row3 col4\" >8.48</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col5\" class=\"data row3 col5\" >3.93</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow3_col6\" class=\"data row3 col6\" >0.46</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row4\" class=\"row_heading level0 row4\" >USD SEK</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col0\" class=\"data row4 col0\" >OptionType.Put</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col1\" class=\"data row4 col1\" >8.11</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col2\" class=\"data row4 col2\" >8.55</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col3\" class=\"data row4 col3\" >0.67</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col4\" class=\"data row4 col4\" >11.01</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col5\" class=\"data row4 col5\" >5.19</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow4_col6\" class=\"data row4 col6\" >0.47</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row5\" class=\"row_heading level0 row5\" >GBP USD</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col0\" class=\"data row5 col0\" >OptionType.Call</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col1\" class=\"data row5 col1\" >1.41</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col2\" class=\"data row5 col2\" >1.33</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col3\" class=\"data row5 col3\" >0.72</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col4\" class=\"data row5 col4\" >11.19</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col5\" class=\"data row5 col5\" >5.37</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow5_col6\" class=\"data row5 col6\" >0.48</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row6\" class=\"row_heading level0 row6\" >USD JPY</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col0\" class=\"data row6 col0\" >OptionType.Put</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col1\" class=\"data row6 col1\" >100.04</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col2\" class=\"data row6 col2\" >104.36</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col3\" class=\"data row6 col3\" >0.18</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col4\" class=\"data row6 col4\" >8.49</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col5\" class=\"data row6 col5\" >4.13</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow6_col6\" class=\"data row6 col6\" >0.49</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row7\" class=\"row_heading level0 row7\" >USD CHF</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col0\" class=\"data row7 col0\" >OptionType.Put</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col1\" class=\"data row7 col1\" >0.87</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col2\" class=\"data row7 col2\" >0.91</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col3\" class=\"data row7 col3\" >0.46</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col4\" class=\"data row7 col4\" >7.43</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col5\" class=\"data row7 col5\" >4.13</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow7_col6\" class=\"data row7 col6\" >0.56</td>\n",
       "            </tr>\n",
       "            <tr>\n",
       "                        <th id=\"T_12672f68_33f8_11eb_963b_00505611250clevel0_row8\" class=\"row_heading level0 row8\" >EUR USD</th>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col0\" class=\"data row8 col0\" >OptionType.Call</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col1\" class=\"data row8 col1\" >1.25</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col2\" class=\"data row8 col2\" >1.20</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col3\" class=\"data row8 col3\" >0.53</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col4\" class=\"data row8 col4\" >7.56</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col5\" class=\"data row8 col5\" >4.35</td>\n",
       "                        <td id=\"T_12672f68_33f8_11eb_963b_00505611250crow8_col6\" class=\"data row8 col6\" >0.58</td>\n",
       "            </tr>\n",
       "    </tbody></table>"
      ],
      "text/plain": [
       "<pandas.io.formats.style.Styler at 0x2133992ea08>"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from gs_quant.timeseries import volatility\n",
    "\n",
    "bf = binaries.to_frame()\n",
    "bf.index = bf.index.droplevel(0)\n",
    "bf = bf[['pair', 'option_type', 'strike_price']]\n",
    "bf['ccy'] = [x.name for x in bf.index]\n",
    "bf['spot'] = list(spot)\n",
    "\n",
    "vols = pd.Series({ccy: volatility(row, len(row) - 1).iloc[0] for ccy, row in df.iteritems()}, name='realized_vol')\n",
    "bf = pd.concat([bf.set_index('ccy'), r2, vols], axis=1).dropna()\n",
    "bf['% otms'] = abs(bf.strike_price / bf.spot - 1) * 100 \n",
    "bf['% otms (vol norm)'] =  bf['% otms'] / bf['realized_vol']\n",
    "\n",
    "bf.set_index(['pair']).sort_values(by=['% otms (vol norm)']).style.background_gradient(subset=['% otms (vol norm)'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now, let's plot R-sq vs how far out of the money we need to strike to get a 10x payout. The most attractive trades will be in the top left: crosses that have the highest R^2 and are not as far otm (in green). As we can see below, USDNOK stands out as the best 10x binary implementation of this cyclical theme."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 360x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(5, 10))\n",
    "ax.imshow([[.5, 0], [0, 0]], cmap=plt.cm.YlGn, interpolation='bicubic', extent=[.2, .8, .1, .9])\n",
    "ax.scatter(bf['% otms (vol norm)'], bf['R2'])\n",
    "plt.title('% OTMS vs R^2')\n",
    "plt.xlabel('% OTMS for 10x binary (vol normalized)')\n",
    "plt.ylabel('YTD R-sq vs SPX')\n",
    "for i, row in bf.iterrows():\n",
    "    ax.annotate(row.pair, (row['% otms (vol norm)'], row['R2']))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### What's New\n",
    "  * Check out [the content from our recent event](https://nbviewer.jupyter.org/github/goldmansachs/gs-quant/tree/master/gs_quant/content/events/00_gsquant_meets_markets/01_ideas_for_risk_re_rating/) focused on ideas for vaccine risk re-rating\n",
    "  * *New* [Reports and Screens](https://nbviewer.jupyter.org/github/goldmansachs/gs-quant/tree/master/gs_quant/content/reports_and_screens) content - please share your feedback on screens you'd like to see\n",
    "  * *New* index curve shift scenario,  [example here](https://nbviewer.jupyter.org/github/goldmansachs/gs-quant/blob/master/gs_quant/documentation/02_pricing_and_risk/01_scenarios_and_contexts/tutorials/Scenarios.ipynb)"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.4"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
